class_docstr: Cropping layer for 2D input (e.g. picture).
  
  It crops along spatial dimensions, i.e. height and width.
  
  Examples:
  
  >>> input_shape = (2, 28, 28, 3)
  >>> x = np.arange(np.prod(input_shape)).reshape(input_shape)
  >>> y = keras.layers.Cropping2D(cropping=((2, 2), (4, 4)))(x)
  >>> y.shape
  (2, 24, 20, 3)
  
  Args:
      cropping: Int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints.
          - If int: the same symmetric cropping is applied to height and
            width.
          - If tuple of 2 ints: interpreted as two different symmetric
            cropping values for height and width:
            `(symmetric_height_crop, symmetric_width_crop)`.
          - If tuple of 2 tuples of 2 ints: interpreted as
            `((top_crop, bottom_crop), (left_crop, right_crop))`.
      data_format: A string, one of `"channels_last"` (default) or
          `"channels_first"`. The ordering of the dimensions in the inputs.
          `"channels_last"` corresponds to inputs with shape
          `(batch_size, height, width, channels)` while `"channels_first"`
          corresponds to inputs with shape
          `(batch_size, channels, height, width)`.
          When unspecified, uses `image_data_format` value found in your Keras
          config file at `~/.keras/keras.json` (if exists). Defaults to
          `"channels_last"`.
  
  Input shape:
      4D tensor with shape:
      - If `data_format` is `"channels_last"`:
        `(batch_size, height, width, channels)`
      - If `data_format` is `"channels_first"`:
        `(batch_size, channels, height, width)`
  
  Output shape:
      4D tensor with shape:
      - If `data_format` is `"channels_last"`:
        `(batch_size, cropped_height, cropped_width, channels)`
      - If `data_format` is `"channels_first"`:
        `(batch_size, channels, cropped_height, cropped_width)`
code: def get_config(self):
      config = {
          "cropping": self.cropping,
          "data_format": self.data_format,
      }
      base_config = super().get_config()
      return {**base_config, **config}
  
file_path: keras/keras/layers/reshaping/cropping2d.py
imports: from keras import backend
  from keras.api_export import keras_export
  from keras.layers.input_spec import InputSpec
  from keras.layers.layer import Layer
  from keras.utils import argument_validation
label_desc: Use image node_id 4 for calling the Cropping2D obj's underlying member method code with example usage: obj.get_config() and returns: dict